{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load Python packages\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import json\n",
    "import topojson\n",
    "import networkx as nx\n",
    "\n",
    "# packages for plotting\n",
    "import matplotlib.pyplot as plt \n",
    "from descartes import PolygonPatch\n",
    "from shapely.geometry import shape\n",
    "import pyproj    \n",
    "import shapely.ops as ops\n",
    "from functools import partial"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load geographic data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load shapefile data of Yemen's districts for plotting\n",
    "# shapefile data encodes the shapes (geographic boundaries) of an area to allow for map plotting\n",
    "with open('data_general/yem-adm2-json-1.json') as json_file:\n",
    "    jdata = json_file.read()\n",
    "    topoJSON = json.loads(jdata)\n",
    "topoJSON.keys()\n",
    "\n",
    "topo_features = topoJSON['objects']['ADM2']['geometries']\n",
    "scale = topoJSON['transform']['scale']\n",
    "translation = topoJSON['transform']['translate']\n",
    "\n",
    "geoJSON = dict(type='FeatureCollection', features=[])\n",
    "for k, tfeature in enumerate(topo_features):\n",
    "    geo_feature = dict(id=k, type=\"Feature\")\n",
    "    geo_feature['properties'] = tfeature['properties']\n",
    "    geo_feature['geometry'] = topojson.geometry(tfeature, topoJSON['arcs'], scale, translation)    \n",
    "    geoJSON['features'].append(geo_feature)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load shapefile data of Yemen's governorates for plotting\n",
    "# shapefile data encodes the shapes (geographic boundaries) of an area to allow for map plotting\n",
    "with open('data_general/yem-adm1-json-2.json') as json_file:\n",
    "    jdata = json_file.read()\n",
    "    topoJSON = json.loads(jdata)\n",
    "topoJSON.keys()\n",
    "\n",
    "topo_features = topoJSON['objects']['ADM1']['geometries']\n",
    "scale = topoJSON['transform']['scale']\n",
    "translation = topoJSON['transform']['translate']\n",
    "\n",
    "geoJSON_gov = dict(type='FeatureCollection', features=[])\n",
    "for k, tfeature in enumerate(topo_features):\n",
    "    geo_feature = dict(id=k, type=\"Feature\")\n",
    "    geo_feature['properties'] = tfeature['properties']\n",
    "    geo_feature['geometry'] = topojson.geometry(tfeature, topoJSON['arcs'], scale, translation)    \n",
    "    geoJSON_gov['features'].append(geo_feature)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load district-level population data, provided by UN OCHA\n",
    "pop = pd.read_excel('data_general/cso_2016_population_projection_sexage_disagreggated.xlsx', \n",
    "                    sheet_name='2016 Population by District', header=[1])\n",
    "pop = pop.iloc[:-1]\n",
    "pop = pop.set_index('District P-Code')\n",
    "\n",
    "# scale 2016 district-level populations down to 2010 levels\n",
    "pop_2010 = 23607000\n",
    "scaler = pop_2010 / pop['TOTAL'].sum()\n",
    "pop.loc[:, 'TOTAL'] = pop.loc[:, 'TOTAL'] * scaler\n",
    "\n",
    "max_pop = pop['TOTAL'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:278: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  type(ring)(zip(*func(*zip(*ring.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:278: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  type(ring)(zip(*func(*zip(*ring.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:278: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  type(ring)(zip(*func(*zip(*ring.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:278: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  type(ring)(zip(*func(*zip(*ring.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "/opt/miniconda3/envs/drones/lib/python3.12/site-packages/shapely/ops.py:276: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n",
      "  shell = type(geom.exterior)(zip(*func(*zip(*geom.exterior.coords))))\n"
     ]
    }
   ],
   "source": [
    "# get population density by district (population of the district divided by area of the district)\n",
    "# the shapefile data provides district areas\n",
    "density = {}\n",
    "for feature in geoJSON['features']:\n",
    "    poly = feature['geometry']\n",
    "    district_id = float(feature['properties']['HRPcode'][2:])\n",
    "    district_pop = pop.loc[district_id]['TOTAL']\n",
    "\n",
    "    geom = shape(poly)\n",
    "    geom_area = ops.transform(\n",
    "    partial(\n",
    "        pyproj.transform,\n",
    "        pyproj.Proj(init='EPSG:4326'),\n",
    "        pyproj.Proj(\n",
    "            proj='aea',\n",
    "            lat_1=geom.bounds[1],\n",
    "            lat_2=geom.bounds[3])), geom)\n",
    "    district_area = (geom_area.area / 1000000.)    # area in km^2\n",
    "    \n",
    "    density[district_id] = district_pop / district_area\n",
    "density = pd.Series(density)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot proximal individual locations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# read in drone strike data to get drone strike coordinates\n",
    "# subset of 74 strikes was compiled from the Bureau of Investigative Journalism and the New America think tank\n",
    "# see paper for details\n",
    "strikes = pd.read_csv('data_general/drone_strike_data.csv', engine='python')\n",
    "strike_locs = strikes[['latitude', 'longitude']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# read in locations of proximal individuals at the time of each strike and 24 hours later\n",
    "locs_t0 = pd.read_csv('data_mobility/eyewitness_locs_at_call.csv', index_col=[0,1])\n",
    "locs_t24 = pd.read_csv('data_mobility/eyewitness_locs_plus_24.csv', index_col=[0,1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Time#Start#Datetime</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">1</th>\n",
       "      <th>22439373</th>\n",
       "      <td>2010-01-12 10:40:03</td>\n",
       "      <td>14.58659</td>\n",
       "      <td>46.06224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17118463</th>\n",
       "      <td>2010-01-12 10:40:24</td>\n",
       "      <td>14.58659</td>\n",
       "      <td>46.06224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8719725</th>\n",
       "      <td>2010-01-12 10:41:01</td>\n",
       "      <td>14.58659</td>\n",
       "      <td>46.06224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12723265</th>\n",
       "      <td>2010-01-12 10:41:05</td>\n",
       "      <td>14.58659</td>\n",
       "      <td>46.06224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21504547</th>\n",
       "      <td>2010-01-12 10:41:49</td>\n",
       "      <td>14.58659</td>\n",
       "      <td>46.06224</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Time#Start#Datetime  Latitude  Longitude\n",
       "1 22439373  2010-01-12 10:40:03  14.58659   46.06224\n",
       "  17118463  2010-01-12 10:40:24  14.58659   46.06224\n",
       "  8719725   2010-01-12 10:41:01  14.58659   46.06224\n",
       "  12723265  2010-01-12 10:41:05  14.58659   46.06224\n",
       "  21504547  2010-01-12 10:41:49  14.58659   46.06224"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# for example, anonymized proximal individual 22439373 made a call at 2010-01-12 10:40:03 after the first strike,\n",
    "# using the cell tower located at (14.58659, 46.06224)\n",
    "locs_t0.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Latitude     14.58659\n",
       "Longitude    46.06224\n",
       "Name: (1, 22439373), dtype: float64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 24 hours after the strike, anonymized proximal individual 22439373 was still located at (14.58659, 46.06224)\n",
    "locs_t24.loc[1,22439373]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# build a bipartite graph where one set of nodes correspond to proximal individuals at the time of the strike and\n",
    "# the other set of the nodes correspond to the same individuals 24 hours later. edges therefore correspond\n",
    "# to their movement in between. the edges will be used for plotting\n",
    "\n",
    "# merge proximal individual locations at time of strike and 24 hours later\n",
    "locs_all = locs_t0.reset_index().merge(locs_t24.reset_index(), left_on=['level_0','level_1'], \n",
    "                                       right_on=['level_0','level_1'], how='inner')\n",
    "\n",
    "# build bipartite graph\n",
    "G = nx.DiGraph()\n",
    "pos = {}\n",
    "for idx, row in locs_all.iterrows():\n",
    "    node0 = str(row['level_0']) + str(row['level_1']) + '#0'\n",
    "    node1 = str(row['level_0']) + str(row['level_1']) + '#1'\n",
    "    \n",
    "    # Check for circular loops\n",
    "    if node0 != node1:\n",
    "        G.add_edge(node0, node1)\n",
    "        pos[node0] = [row['Longitude_x'], row['Latitude_x']]\n",
    "        pos[node1] = [row['Longitude_y'], row['Latitude_y']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "''"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# figure 3a: plot locations of proximal individuals at the time of their calls after strikes\n",
    "\n",
    "fig = plt.figure(figsize=(12, 8)) \n",
    "ax = fig.gca()\n",
    "  \n",
    "# plot Yemen's districts and shade populated regions grey (population density greater than 30 people per km^2)\n",
    "for feature in geoJSON['features']:\n",
    "    if feature['properties']['GovNameEn'] == 'Socotra':\n",
    "        continue\n",
    "    poly = feature['geometry']\n",
    "    district_id = float(feature['properties']['HRPcode'][2:])\n",
    "    if density[district_id] > 30:    # shade populated regions\n",
    "        f = 'Grey'\n",
    "    else:\n",
    "        f = 'None'\n",
    "    ax.add_patch(PolygonPatch(poly, fc=f, ec='Grey', alpha=0.2, zorder=0))\n",
    "    \n",
    "# plot Yemen's governorates\n",
    "for feature in geoJSON_gov['features']:\n",
    "    if feature['properties']['Governor_1'] == 'Socotra':\n",
    "        continue\n",
    "    poly = feature['geometry']\n",
    "    ax.add_patch(PolygonPatch(poly, fc='None', ec='Black', alpha=1, zorder=0))\n",
    "\n",
    "# plot locations of proximal individuals in blue and locations of strikes in red\n",
    "plt_l = plt.scatter(locs_t0['Longitude'], locs_t0['Latitude'], s=30, c='blue', edgecolor='None', alpha=0.6, zorder=4)\n",
    "plt_s = plt.scatter(strike_locs['longitude'], strike_locs['latitude'], s=100, c='red', marker='x', alpha=1, zorder=6)\n",
    "\n",
    "ax.axis('scaled')\n",
    "ax.set_xlim([42, 53.3])\n",
    "ax.set_ylim([12.4, 19.3])\n",
    "ax.axis('off')\n",
    "ax.legend((plt_l, plt_s), ('Proximal individual', 'Drone strike'), loc='lower right')\n",
    "fig.savefig('figures/figure3_t0.png', bbox_inches='tight', format='png', dpi=600)\n",
    "''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "''"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# figure 3b: plot locations of proximal individuals 24 hours after time of call after strikes\n",
    "# edges show movement over the past 24 hours\n",
    "\n",
    "fig = plt.figure(figsize=(12, 8)) \n",
    "ax = fig.gca()\n",
    "  \n",
    "# plot Yemen's districts and shade populated regions grey (population density greater than 30 people per km^2)\n",
    "for feature in geoJSON['features']:\n",
    "    if feature['properties']['GovNameEn'] == 'Socotra':\n",
    "        continue\n",
    "    poly = feature['geometry']\n",
    "    district_id = float(feature['properties']['HRPcode'][2:])\n",
    "    if density[district_id] > 30:    # shade populated regions\n",
    "        f = 'Grey'\n",
    "    else:\n",
    "        f = 'None'\n",
    "    ax.add_patch(PolygonPatch(poly, fc=f, ec='Grey', alpha=0.2, zorder=0))\n",
    "\n",
    "# plot Yemen's governorates\n",
    "for feature in geoJSON_gov['features']:\n",
    "    if feature['properties']['Governor_1'] == 'Socotra':\n",
    "        continue\n",
    "    poly = feature['geometry']\n",
    "    ax.add_patch(PolygonPatch(poly, fc='None', ec='Black', alpha=1, zorder=0))\n",
    "\n",
    "# plot locations of proximal individuals in blue and locations of strikes in red\n",
    "plt_l = plt.scatter(locs_t24['Longitude'], locs_t24['Latitude'], \n",
    "                    s=30, c='blue', edgecolor='None', alpha=0.6, zorder=5)\n",
    "plt_s = plt.scatter(strike_locs['longitude'], strike_locs['latitude'], s=100, c='red', marker='x', alpha=1, zorder=6)\n",
    "\n",
    "# plot edges showing movement of proximal individuals over the past 24 hours\n",
    "nx.draw_networkx_edges(G, pos, ax=ax, alpha=0.1, node_size=30, edge_color='C0')\n",
    "\n",
    "ax.axis('scaled')\n",
    "ax.set_xlim([42, 53.3])\n",
    "ax.set_ylim([12.4, 19.3])\n",
    "ax.axis('off')\n",
    "ax.legend((plt_l, plt_s), ('Proximal individual', 'Drone strike'), loc='lower right')\n",
    "fig.savefig('figures/figure3_t24.png', bbox_inches='tight', format='png', dpi=600)\n",
    "''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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